Method and device for reducing intermediate points in a polygon

ABSTRACT

One aspect relates to a method for reducing intermediate nodes in a polygonal chain with one or a plurality of intermediate nodes of a set of intermediate nodes between a starting node and an end node. In addition to the attributes of longitude and latitude, at least one further attribute with an attribute value and an attribute direction of a set of further attributes is assigned to the starting node, the end node and every intermediate node of the set of intermediate nodes. The attributes can be a gradient, a curve-radius or an altitude.

BACKGROUND

The invention relates to the field of driving assistance systems. Theinvention relates in particular to a method and a device for complexityreduction of map data represented by means of polygons for an electronichorizon application.

Modern motor vehicles have a multiplicity of different drivingassistance functions which assist the driver in planning routes or inguiding the vehicle. ADAS (Advanced Driver Assistance Systems) have beendeveloped to increase the comfort, efficiency, safety and driversatisfaction when driving. These are supplementary electronic devices inmotor vehicles which assist the driver in particular driving situations.ADAS's relate, for example, to adaptive headlamp settings, adaptivespeed control, warnings when leaving the traffic lane, curve warnings,speed limit warning. ADAS's here access, partially or fullyautonomously, the drive, control or signaling equipment of the vehicle,and warn the driver through appropriate human-machine interfaces shortlybefore or during critical situations. Some ADAS's here use a range ofsensors such as RADAR, infrared, ultrasonic and optical sensors such asdigital video cameras and LIDAR.

Some ADAS's use digital map data. The digital map supplies, inparticular, information about the road network, the road geometry, roadconditions and the terrain surrounding a vehicle. Digital map datasupply valuable information that cannot be captured by means of sensors,such as the curvature, gradient, speed limits that are not displayed,traffic lane boundaries etc. In addition to this, a certain predictionfunction that goes beyond the capture possibilities of sensors or theview of the driver belongs to a digital map.

ADAS's that require digital map data usually use a geographic databasethat is associated with the navigation system of the vehicle. Thisdatabase of the navigation system contains data for representing a roadnetwork in a region, in particular the geographic data including thealtitude of roads, road junctions, turning restrictions at roadjunctions, road names, and speed Limits.

The database of the navigation system can contain more data than arenecessary for an ADAS application. An application of this sort can be aneHorizon application that determines an electronic horizon. Anelectronic horizon is an assembly of roads and road junctions thatextend from a current vehicle position to an extent that is determinedby an eHorizon application. The assembly of roads and road junctions ismade up of potential paths that the vehicle can follow from the currentposition. As a rule, an eHorizon system can only process map data with alimited degree of complexity, while on the other hand the map data mustalso satisfy accuracy requirements.

Map data can be represented by means of geometric figures such aspolygons in two-dimensional space or polyhedrons in three-dimensionalspace. A polygon, or a polygonal chain, can here be defined as a set ofconnected segments that yield a form. A polygon can also be defined by aset of nodes that yield a form when they are connected by segments. Apolygon can also be defined by a set of segments and nodes that yield aform when they complement each other, A node is a point at which twosegments meet, A polygon can be described with an arbitrary number ofnodes. Two segments that meet at an angle of 180° form a larger segmentthat includes the two segments. A segment is thus a connection or anedge of two points.

Road networks can be described by nodes and edges, where a road segmentis bounded by a starting node and an end node, and the edge can comprisea detailed geometrical shaping such as a curvature. The detailedgeometric shaping comes about through intermediate nodes (control nodesor shape points). The nodes and intermediate nodes are described bylatitude (geographic latitude) and longitude (geographic latitude), andthus by their position. The nodes can in addition be described throughthe attributes of gradient, altitude and curve-radius, A road segmentcan comprise a plurality of curves. A road segment can be described byB-splines or cubic. Bezier curves. A Bezier curve is described by fourcontrol nodes, wherein the last control node of a preceding Bezier curveis the same as the first control point for the following Bezier curve.

A road segment can be approximated by polygons. In this case, a roadsegment consists of a plurality of connected segments, whose arrangementis defined by the nodes and intermediate nodes, with at least theadditional attribute of altitude.

If an eHorizon system uses map data that are represented by polygons,altitude information may become a necessity, for example in order toregulate the drive of the vehicle when driving up and down hills. Themaps must not, on the other hand, be too complicated, meaning that thenumber of intermediate nodes must not be unnecessarily high, in order toguarantee real-time processing.

Methods are known in the prior art for simplifying polygons or polygonalchains. The methods serve for curve-smoothing and the generalization ofmaps. These are referred to below as line generalization methods. Oneclass of line generalization methods considers a polygon as a whole, andprogresses to finer approximations.

One known line generalization method of this sort is the 2DDouglas-Peucker algorithm, whose aim is to simplify a polygonal chaingiven by a sequence of points by omitting individual points in such away that the basic form is retained. The initial polygon is divided forthis purpose into two segments which for their part then pass throughthe algorithm. It is thus a recursive method.

The 2D Douglas-Peucker algorithm is described with reference to FIG. 1which shows a polygon in its initial form 0 and in the different stagesof approximation 1 to 4, with a total of n=8 nodes, A segment betweenthe starting node K1 and the end node K2 is considered as a firstapproximation. To check whether this approximation is adequate, theintermediate node from amongst the n−2 intermediate nodes that has thegreatest distance from the segment between K1 and K2 is searched for. Atapproximation stage 1, this is S2, with the distance illustrated as aperpendicular. If this distance is smaller than a tolerance, theapproximation is adequate, and all the other intermediate nodes can bediscarded. That is not the case here. S2 is therefore retained, and theapproximation is refined.

As a second approximation, a segment between K1 and S2 is considered, asis a segment between S2 and K2. It will certainly be found here that S1has a distance from the segment between K1 and S2 that is smaller thanthe tolerance. S1 can be discarded. The node with the greatest distancefrom the segment between S2 and K2 is S4. The distance is greater thanthe tolerance. The segment between S2 and K2 must therefore be refinedfurther.

The third approximation consists of a segment between K1 and S2, asegment between S2 and S4, and a segment between S4 and K2. Aninvestigation is made as to whether this approximation is adequate inthe third approximation stage. This is not the case for the segmentbetween S4 and K2, since the distance from S6 to this segment exceedsthe tolerance. This segment must consequently be refined further.

The result can be seen in the fourth approximation stage with a fourthapproximation with a segment between K1 and S2, a segment between S2 andS3, and a segment between S4 and S6, as well as a segment between S6 andK2.

The Douglas-Peucker algorithm is thus a two-dimensional linegeneralization method, wherein only the latitude and longitude ofsequential intermediate nodes are considered.

The restriction to these attributes however does not satisfy therequirements of an electronic horizon. The required tolerances forgradient, curve-radius and altitude can in particular not be guaranteed,since these are not considered at all in the two-dimensionalDouglas-Peucker algorithm.

BRIEF SUMMARY

It is therefore the object of the invention to give a method and anapparatus for reducing intermediate points that satisfy the requirementsof an eHorizon application.

This object is achieved with a method according to the independentmethod claim and a device according to the independent device claim. Thedependent claims relate to advantageous configurations.

One aspect relates to a method for reducing intermediate nodes in apolygonal chain with one or a plurality of intermediate nodes of a setof intermediate nodes between a starting node and an end node. Inaddition to the attributes of longitude and latitude, at least onefurther attribute with an attribute value and an attribute direction ofa set of further attributes is assigned to the starting node, the endnode and every intermediate node of the set of intermediate nodes. Theattributes can be a gradient, a curve-radius or an altitude. In one ormore processors, for each intermediate node starting from the startingnode, the following method steps are carried out: comparing theattribute direction of the at least one further attribute of anintermediate node with the attribute direction of the at least onefurther attribute of the immediately preceding node; marking theintermediate node as a significant node if the comparison yields adirection change of the attribute direction; and applying a linegeneralization method with reference to the longitude and latitudeattributes, wherein the intermediate nodes that are marked assignificant nodes may not be removed. The line generalization methodcan, in particular, be the Douglas-Peucker algorithm.

Assuming that the polygonal chain models a straight segment of road thathas a specific altitude profile, i.e. in addition to the attributes oflatitude and longitude, a value for the altitude is additionallyassigned to each node and intermediate node. A direction change withrespect to the attribute of altitude means that the altitude value ofthe intermediate node concerned must relate to an at least localaltitude maximum or an at least local altitude minimum. If theDouglas-Peucker is applied to a road segment that is straight in termsof the attributes of latitude and altitude, without taking into accountintermediate nodes that have been classified as significant, thereremains a single segment between the starting node and the end node,since, in the case of a straight road segment, there is precisely novariation perpendicular to the connection between the starting point andend point. All the intermediate nodes are eliminated, and with thesealso all the altitude information that is relevant for an ADAS. Becauseat least those intermediate nodes at which an at least local altitudeminimum or an at least local altitude maximum is present are marked assignificant, and these must not be removed by the Douglas-Peuckeralgorithm, the most important altitude information is retained.

A direction change is defined in relation to the immediately precedingnode.

A direction change relating to the attribute of gradient is defined asfrom an upward gradient to a downward gradient or from a downwardgradient to an upward gradient.

A direction change for the curve-radius is defined as from acurve-radius to the left to a curve-radius to the right, or from acurve-radius to the right to a curve-radius to the left.

A direction change for the altitude is defined as a rising altitude to afalling altitude or a falling altitude to a rising altitude.

In addition to the tolerance that is considered in the Douglas-Peuckeralgorithm with respect to longitude and latitude, and the directionchanges of further attributes, the method can also be supplemented by atolerance consideration relating to the further attributes.

According to one aspect, prior to application of the line generalizationmethod, the following method steps are carried out in addition in one ormore processors, for each intermediate node of the set of intermediatenodes, starting from the starting node: Determining a difference betweenthe value of the at least one further attribute of an intermediate nodeand the value of the at least one further attribute of a preceding node,wherein the preceding node is a proximate preceding starting node or aproximate preceding intermediate node that has not yet been removed;marking the intermediate node as a significant node if the differenceexceeds a threshold value, otherwise removing the intermediate node fromthe set of intermediate nodes.

Only such intermediate nodes at which the difference between thegradient, altitude or curve-radius in comparison with the preceding noderemains below a threshold value are thus removed from a gradientprofile, an altitude profile or a curve profile, wherein the precedingnode is a starting node or an intermediate node that has not yet beenremoved.

According to a further aspect, prior to application of the linegeneralization method, the following method steps are carried out inaddition in one or more processors, for each intermediate node of theset of intermediate nodes, starting from the starting node; determininga first difference between the value of the at least one furtherattribute of an intermediate node and the value of the at least onefurther attribute of a preceding node, wherein the preceding node is aproximate preceding starting node or a proximate preceding intermediatenode that has not been removed; determining a second difference betweenthe value of the at least one further attribute of the immediatelysucceeding node and the value of the at least one further attribute ofthe intermediate node; determining a difference between the firstdifference and the second difference; and marking the intermediate nodeas a significant node if the difference exceeds a threshold value,otherwise removing the intermediate node.

The at least one additional attribute can, in particular, be analtitude. The gradient of the segment between intermediate nodes andpreceding nodes, and the gradient of the segment between subsequentnodes and intermediate nodes, are thus determined. The difference ofthese segment gradients is compared with the threshold value, i.e. thegreatest possible tolerance.

According to a further aspect, prior to application of the linegeneralization method, the following method steps are carried out inaddition in one or more processors, for each intermediate node of theset of intermediate nodes, starting from the starting node: determininga first difference between the value of the at least one furtherattribute of an intermediate node and the value of the at least onefurther attribute of a preceding node, wherein the preceding node is aproximate preceding starting node or a proximate preceding intermediatenode that has not been removed; determining a second difference betweenthe value of the at least one further attribute of the immediatelysucceeding node and the value of the at least one further attribute ofthe preceding node; determining a difference between the firstdifference and the second difference; and marking the intermediate nodeas a significant node if the difference exceeds a threshold value,otherwise removing the intermediate node.

The at least one additional attribute can, in particular, be analtitude. The gradient between intermediate nodes and preceding nodes,and the gradient between subsequent nodes and preceding nodes, are thusdetermined. The difference between these gradients is compared with thethreshold value.

According to one aspect, several attributes of the set of furtherattributes can be considered in the same way as described above.

One aspect relates to a method for reducing intermediate nodes in apolygonal chain with one or a plurality of intermediate nodes of a setof intermediate nodes between a starting node and an end node, wherein,in addition to the attributes of longitude and latitude, at least onefurther attribute with an attribute value and an attribute direction ofa set of further attributes is assigned to the starting node, the endnode and every intermediate node of the set of intermediate nodes, inone or more processors, for each intermediate node, the starting node,the following method steps are carried out starting from.

Comparing the attribute direction of the at least one further attributeof an intermediate node with the attribute direction of the at least onefurther attribute of the immediately preceding node; marking theintermediate node as a significant node if the comparison yields adirection change of the attribute direction; applying a line reductionmethod with reference to the at least one further attribute, and aprojection of the polygonal chain either onto the longitude or thelatitude, wherein the intermediate nodes marked as significant must notbe removed; marking intermediate nodes remaining after application ofthe line reduction method as significant nodes; and applying the linegeneralization method with reference to the longitude and latitudeattributes, wherein the intermediate nodes that are marked assignificant nodes must not be removed.

As soon as a direction change of an attribute direction, thecorresponding intermediate node is marked as a significant node. Thesignificant node must not be removed during application of the twofollowing line generalization methods. The line generalization methodwith respect to the at least one further attribute and the projection ofthe polygonal chain onto either the longitude or the latitude is usedfor the further determination of significant nodes which must not beremoved in the following line generalization method with respect to thelongitude and latitude.

The at least one further attribute is the altitude. The linegeneralization method is the Douglas-Peucker algorithm. This means thatthe Douglas-Peucker algorithm is first applied to the altitude profile,wherein, according to the method, the removal of at least local altitudemaxima or of at least local altitude minima is ruled out. The remainingintermediate nodes are necessary in order to accurately represent thealtitude profile, and must not be removed in the further method. Thealtitude profile describes the altitude against the projection of thepolygonal chain either onto the latitude or the longitude. TheDouglas-Peucker algorithm is now applied once again, but this time withrespect to the longitude and latitude, wherein, in addition to thesignificant intermediate nodes resulting from direction changes, thesignificant intermediate nodes determined through the application of theDouglas-Peucker algorithm with respect to altitude and projection mustnot be removed either. This results in a polygonal chain which isoptimally reduced in terms of longitude and latitude and whichnevertheless provides sufficiently accurate altitude information for anelectronic horizon.

One aspect relates to a device with a processor that is configured toexecute a method as described above. The method can be represented inprogram instructions that the processor carries out.

BRIEF DESCRIPTION OF THE FIGURES

The invention will be described below on the basis of exemplaryembodiments and with reference to figures, Here:

FIG. 1 shows method stages of the Douglas-Peucker algorithm applied to apolygon;

FIG. 2 shows a block diagram of an ADAS architecture;

FIG. 3 shows a block diagram of possible software applications in theADAS architecture;

FIG. 4 shows a section of terrain modeled by a polygon;

FIG. 5 shows examples for direction changes for different attributes;and

FIG. 6 shows a flow diagram/program flow chart of the method.

DETAILED DESCRIPTION

FIG. 2 shows a block diagram of an ADAS architecture 200. The ADASarchitecture 200 has a map and positioning engine 204 and driverassistance applications 214. The map and positioning engine 204 can be asingle module; or it can be divided into various packages. It can alsobe integrated into other packages such as a sensor package. The map andpositioning engine 204 comprises a processor 102, a positioning system204, a map database 206, a communication system 208 with a communicationinterface for mobile communication in particular and a data businterface 210, The processor 202 receives data from the positioningsystem 204, the map database 206, the communication system 208 and thedata bus interface 210, and processes these by means of softwareprograms or software applications, of which some are described furtherbelow with reference to FIG. 3.

The processor 202 provides processed data over the data bus interface210 and the data bus 212 to the driver assistance applications 214. Oneof the driver assistance applications 214 can be an electronic horizon.The positioning system 214 uses (WS technology and a gyroscope, and canfurthermore comprise sensors for detection of the vehicle speed,direction, orientation etc. The positioning system 214 makes thisinformation available to the processor 202. Some of the softwareapplications running on the processor need this information.

The geographic map bank 206 contains map data, as are usual for anavigation system. The map data contain in particular data relating toroads and road junctions in the form of road segments between a startingnode and an end node and a geometric shaping by means of intermediatenodes between starting node and end node. The road segments can bemodeled as polygons.

FIG. 3 shows a block diagram with various software applications 300 thatcan run on the processor 202. The software applications contain a mapaccess application 302, a map update application 304, a vehiclepositioning application 306 and an eHorizon application 308.

The map access application 302 provides map access data of thegeographic map database 206. The map access application 302 receives aquery from the processor 202 for a map extract, and calls the mapextract up by means of the map access data in the geographic mapdatabase 206.

The map update application 304 serves to update the geographic mapdatabase 206. Map extracts that no longer contain any current map datacan be exchanged. The geographic map database 206 can moreover beextended with further map extracts. The map update application providesa communication channel for this purpose between the communicationsystem 208 and the geographic map database, via which the current mapdata can be transferred.

The vehicle positioning application 306 determines the position of thevehicle relative to the road network which is represented by thegeographic map database 206. The vehicle positioning application 306uses the positioning data generated by the positioning system 204, andcompares these with the map data from the geographic map database 206 bymeans of a map comparison algorithm.

The eHorizon application 308 calculates an electronic horizon. It usesmap data from the electronic map database 206 for this purpose. The mapdata, however, are present with a complexity that is too great for theeHorizon application, since this should calculate an electronic horizonin real time. The complexity of the map data must therefore be reduced,but nevertheless satisfy certain requirements for accuracy. A complexityreduction of this sort of a road segment modeled by a polygonal chain isdescribed below with reference to FIG. 4,

FIG. 4 a) shows a sectional diagram 400 of a terrain with a road thatruns straight between the starting point K1 and the end point K2, alongwhich a vehicle 402 is moving. The road runs in the direction of a lineof latitude, and thus exhibits no variation in the direction of a lineof longitude. The road is not, however, flat, but passes over a hill.The road thus has an altitude profile. The road is to be modeled by apolygon, whose starting node K1, intermediate nodes Z1, Z2, . . . , Z8and end node K2 are illustrated in plan view,

FIG. 4 b) shows the associated polygon with the associated arrangementof the intermediate points in the sectional view. The polygon has aglobal maximum at the intermediate node Z4. The segment between theintermediate nodes Z4 and Z5 models a top of the hill. The segmentbetween the intermediate nodes Z5 and Z6 has a strong downward gradient.

Through applying the 2D Douglas-Peucker algorithm with reference to theattributes of longitude and latitude to the polygon, the altitudeinformation would be entirely lost, since the road runs straight, andall intermediate nodes Z1, Z2, . . . , Z4 would be removed. Since thealtitude information is relevant in an electronic horizon, significantaltitude information should be retained.

The processor 202 examines whether there is a change in the altitudedirection, i.e. whether a direction change is present in the segmentgradient, for each intermediate node Z1, Z2, . . . , Z4. That is thecase here for intermediate node Z4, since this represents a localaltitude maximum. The intermediate node Z4 is marked as a significantnode, and must not be removed during later application of theDouglas-Peucker algorithm with reference to the attributes of longitudeand latitude. The local maximum of the altitude profile is thusinitially conserved.

The conservation of local maxima or minima of the altitude profile can,however, not be sufficient for an electronic horizon, A more accuratemodeling of the altitude profile is, for example, necessary for a drivecontroller. Further intermediate nodes should therefore be marked assignificant nodes, so that these are not removed when theDouglas-Peucker algorithm is applied with reference to the attributes ofaltitude and longitude. The examination of the intermediate nodes andthe potential marking of said nodes are performed by the processor 202in FIG. 2 which examines, for example, a change in the segment gradient.This is explained with reference to FIG. 4 b).

The first intermediate node starting from the start node K1 isconsidered initially for this purpose. The first intermediate node isintermediate node Z1. The gradient of the segment between K1 and Z1 iscompared with the gradient of the segment between Z1 and Z2, If thechange in the gradient is lower than a threshold value, then Z1 can beremoved from the set of intermediate nodes, otherwise Z1 is marked as asignificant node. The segment gradient can be determined from thealtitude difference between two nodes. The difference in the altitudebetween Z1 and K1, i.e. the gradient of the segment between K1 and Z2,is thus compared with the difference in the altitude between Z2 and Z1,i.e. the gradient of the segment between Z2 and Z1. The change in thegradient is here lower than the threshold value Z1 can therefore beremoved from the set of intermediate nodes.

Z2 is now examined. The segment gradient of the segment between K1 andZ2 and the segment gradient of the segment between Z2 and Z3 areconsidered here. The change of these segment gradients is again lowerthan the threshold value. Z2 can therefore be removed from the set ofintermediate nodes.

Z3 is now examined. The segment gradient of the segment between K1 andZ3 and the segment gradient of the segment between Z3 and Z4 areconsidered here. The change of these segment gradients is again lowerthan the threshold value. Z3 can therefore be removed from the set ofintermediate nodes.

Z5 is now examined. Z4 was already marked as a significant node. Thesegment gradient of the segment between Z4 and Z5 and the segmentgradient of the segment between Z5 and Z6 are considered here. This timethe change of these segment gradients is above the threshold value,since the altitude profile has a strong downward gradient. Z5 istherefore marked as a significant intermediate node, and must not beremoved during later application of the Douglas-Peucker algorithm withreference to the attributes of longitude and latitude.

Z6 is now examined. The segment gradient of the segment between Z5 andZ6 and the segment gradient of the segment between Z6 and Z7 areconsidered here. The change of these segment gradients is again abovethe threshold value, since the altitude profile here has a transitionfrom a strong to a weak downward gradient, Z6 is therefore marked as asignificant intermediate node, and must not be removed during laterapplication of the Douglas-Peucker algorithm with reference to theattributes of longitude and latitude.

Z7 is now examined. The segment gradient of the segment between Z6 andZ7 and the segment gradient of the segment between Z7 and Z8 areconsidered here. The change of these segment gradients is again lowerthan the threshold value. Z7 can therefore be removed from the set ofintermediate nodes.

Z8 is now examined. The segment gradient of the segment between Z7 andZ8 and the segment gradient of the segment between Z8 and K2 areconsidered here. The change of these segment gradients is again lowerthan the threshold value. Z8 can therefore be removed from the set ofintermediate nodes.

A summary of the above method is illustrated in FIG. 4 c).

The result of the method is illustrated in FIG. 4 d), The intermediatenodes Z4, Z5 and Z6 remain, which model the altitude profile withsufficient accuracy for an electronic horizon.

As an alternative to the method described above, the Douglas-Peuckeralgorithm can also be applied first to the altitude profile, i.e. withrespect to the attributes altitude and the projection onto the latitude.Z4 is also first identified as a significant node, since a directionchange of the altitude or the segment gradient is present here. Thefirst approximation here is consequently not a segment between K1 andK2, but a start is made with the second approximation which is given bya first segment between K1 and Z4 and a second segment between Z4 andK2. To check whether this approximation is adequate, the intermediatenode from amongst the intermediate nodes Z1, Z2 and Z3 that has thegreatest distance from the segment between K1 and Z4 is searched for.This is Z1. Since the distance is smaller than a threshold value, theapproximation is adequate, and Z1, Z2, and Z3 can be removed. To checkwhether the second approximation is adequate, the intermediate node fromamongst the intermediate nodes Z5, Z6, Z7 and Z8 that has the greatestdistance from the segment between Z4 and K2 is furthermore searched for.This is Z6. Since the distance is greater than the threshold value, thesecond approximation through the segment between Z4 and K2 is notadequate.

The third approximation is thus a segment between K1 and Z4, a segmentbetween Z4 and Z6, and a segment between Z6 and K2. To check whetherthis approximation is adequate, Z5 is examined to see whether itsdistance from the segment between Z4 and Z6 exceeds a threshold value.Since that is the case here, the approximation is not adequate. Thesegment between Z4 and Z6 must consequently be further refined into twosegments, one between Z4 and Z5 and one between Z5 and Z6. It isfurthermore necessary to check whether the segment between Z6 and K2must be refined further. For this purpose an examination is made as towhich of the intermediate points Z7 and Z8 has the greatest distancefrom the segment between Z5 and K2. This is Z7. Since the distance doesnot exceed a threshold value, Z7 and Z8 can be deleted. This results ina fourth approximation with a segment between K1 and Z4, a segmentbetween Z4 and Z5, a segment between Z5 and Z6, and a segment between Z6and K2.

Z4, Z5 and Z6 thus remain as significant intermediate nodes which mustnot be removed during later application of the Douglas-Peucker algorithmwith reference to the attributes of longitude and latitude.

FIG. 5 graphically clarifies once again the direction change withrespect to the attributes of gradient, curve-radius and altitude.

FIG. 5 a) shows a direction change of the gradient attribute from anupward gradient to a downward gradient. FIG. 5 b) shows a directionchange with reference to the gradient attribute from a downward gradientto an upward gradient. FIG. 5 c) shows a direction change with respectto the attribute of curve-radius from a curve-radius to the left to acurve-radius to the right. FIG. 5 d) shows a direction change withrespect to the attribute of curve-radius from a curve-radius to theright to a curve-radius to the left. FIG. 5 e) shows a direction changewith reference to the attribute of altitude from a rising altitude to afalling altitude, and from a falling altitude to a rising altitude.

An embodiment of the method is explained below with reference to theflow diagram in FIG. 6.

In step 602 the tolerances for the gradient tolSlope, the curvaturetolCurv and the altitude tolAlt are made available. In step 604 thenumber of intermediate nodes is determined. This is identified asmaxKnoten. Reference values for the gradient refSlope, the curvaturerefCurv and the altitude refAlt are read in for the starting node K1 instep 606. In step 608, a loop counter, which operates over the number ofintermediate nodes with index knotenZ, is initialized with the valueone. A check is performed in step 610 as to whether the maximum numberof intermediate nodes has already been exceeded. If this is the case themethod terminates. If this is not the case, the zSlope for the gradient,zCurv for the curvature and zAlt for the altitude are read in for therespective intermediate node. In step 614, these values are comparedwith the values of the reference node, and a check is made as to whethera deviation is still within the tolerance range.

For this purpose a check is made as to whether the absolute magnitude ofthe difference of the gradient, value of the intermediate node and thegradient value of the reference node lies below the tolerance for thegradient: abs(zSlope−refSlope)<toleranceSlope.

For this purpose a check is made as to whether the absolute magnitude ofthe difference of the curvature value of the intermediate node and thecurvature value of the reference node lies below the tolerance for thecurvature: abs(zCurvature−refCurvature)<toleranceCurvature.

For this purpose a check is made as to whether the absolute magnitude ofthe difference of the altitude value of the intermediate node and thealtitude value of the reference node lies below the tolerance for thealtitude: abs(zAltitude−refAltitude)<toleranceAltitude.

In step 614, an additional check is also made as to whether thefollowing supplementary conditions relating to a direction change of thegradient, curvature and altitude are satisfied:

(((zSlope>0 and refSlope>0) or (zSlope<0 and refSlope<0) or (zSlope=0and refSlope=0)) and

((zCurvature>0 and refCurvature>0) or (zCurvature<0 and refCurvature<0)or (zCurvature=0 and refCurvature=0)) and

((zAltitude>0 and refAltitude>0) or (zAltitude<0 and refAltitude<0) or

(zAltitude=0 and refAltitude=0)))

“And” and or in the above combinations refer to logical AND and logicalOR.

If the supplementary conditions are satisfied, there is no directionchange.

If the comparison values for gradient, curvature and altitude lie in thetolerance range, and if the supplementary conditions are satisfied, thenin step 618 the relevant intermediate node is marked as deletable, i.e.it can be removed from the set of intermediate nodes. If this is not thecase, the node is significant, and it is specified as a reference nodefor the next pass through the loop in step 616.

In step 620 the index of the intermediate node is increased by one, andthe loop is started again at step 610.

The aspects and forms of embodiment of the method for reducingintermediate nodes described above can be executed either on a processorof an ADAS architecture installed or located in a target, for example ina vehicle, in order to calculate an ADAS map for an eHorizonapplication, or on an external server, i.e. a dedicated ADAS map iscalculated in advance. The advance calculation of the ADAS map on anexternal server and subsequent transfer to the target have the advantagethat computing time is saved on the target, and the size of the mapdatabase on the target can be reduced.

1. A method for reducing intermediate nodes in a polygonal chain withone or a plurality of intermediate nodes of a set of intermediate nodesbetween a starting node and an end node, wherein, in addition to theattributes of longitude and latitude, at least one further attributewith an attribute value and an attribute direction of a set of furtherattributes is assigned to the starting node, the end node and everyintermediate node of the set of intermediate nodes, the methodcomprising: in one or more processors, for each intermediate node,starting from the starting node: comparing the attribute direction ofthe at least one further attribute of an intermediate node with theattribute direction of the at least one further attribute of theimmediately preceding node; marking the intermediate node as asignificant node if the comparison yields a direction change of theattribute direction; and applying a line generalization method withreference to the longitude and latitude attributes, wherein theintermediate nodes that are marked as significant nodes may not beremoved.
 2. The method as claimed in claim 1, comprising: prior toapplication of the line generalization method, in one or moreprocessors, for each intermediate node of the set of intermediate nodes,starting from the starting node: determining a difference between thevalue of the at least one further attribute of an intermediate node andthe value of the at least one further attribute of a preceding node,wherein the preceding node is a proximate preceding starting node or aproximate preceding intermediate node that has not yet been removed; andmarking the intermediate node as a significant node if the differenceexceeds a threshold value, otherwise removing the intermediate node fromthe set of intermediate nodes.
 3. The method as claimed in claim 1, alsocomprising: prior to application of the line generalization method, inone or more processors, for each intermediate node of the set ofintermediate nodes, starting from the starting node: determining a firstdifference between the value of the at least one further attribute of anintermediate node and the value of the at least one further attribute ofa preceding node, wherein the preceding node is a proximate precedingstarting node or a proximate preceding intermediate node that has notbeen removed; determining a second difference between the value of theat least one further attribute of the immediately succeeding node andthe value of the at least one further attribute of the intermediatenode; determining a difference between the first difference and thesecond difference; and marking the intermediate node as a significantnode if the difference exceeds a threshold value, otherwise removing theintermediate node.
 4. The method as claimed in claim 1, also comprising:prior to application of the line generalization method, in one or moreprocessors, for each intermediate node of the set of intermediate nodes,starting from the starting node: determining a first difference betweenthe value of the at least one further attribute of an intermediate nodeand the value of the at least one further attribute of a preceding node,wherein the preceding node is a proximate preceding starting node or aproximate preceding intermediate node that has not been removed;determining a second difference between the value of the at least onefurther attribute of the immediately succeeding node and the value ofthe at least one further attribute of the preceding node; determining adifference between the first difference and the second difference; andmarking the intermediate node as a significant node if the thirddifference exceeds a threshold value, otherwise removing theintermediate node.
 5. The method as claimed in claim 4, wherein the atleast one further attribute is a gradient or an altitude or acurve-radius.
 6. The method as claimed in claim 5, wherein the set ofattributes comprises two attributes, and wherein the marking of theintermediate node as a significant node and the removal of theintermediate node take place with reference to the two attributes. 7.The method as claimed in claim 1, comprising: a method for reducingintermediate nodes in a polygonal chain with one or a plurality ofintermediate nodes of a set of intermediate nodes between a startingnode and an end node, wherein, in addition to the attributes oflongitude and latitude, at least one further attribute with an attributevalue and an attribute direction of a set of further attributes isassigned to the starting node, the end node and every intermediate nodeof the set of intermediate nodes, the method comprising: in one or moreprocessors, for each intermediate node, starting from the starting node:comparing the attribute direction of the at least one further attributeof an intermediate node with the attribute direction of the at least onefurther attribute of the immediately preceding node; marking theintermediate node as a significant node if the comparison yields adirection change of the attribute direction; applying a line reductionmethod with reference to the at least one further attribute, and aprojection of the polygonal chain either onto the longitude or thelatitude, wherein the intermediate nodes marked as significant must notbe removed; marking intermediate nodes remaining after application ofthe line reduction method as significant nodes; and applying the linegeneralization method with reference to the longitude and latitudeattributes, wherein the intermediate nodes that are marked assignificant nodes must not be removed.
 8. The method as claimed in oneof claim 7, wherein the line generalization method is the DouglasPeucker algorithm.
 9. The method as claimed in one of claim 8, whereinthe polygonal chain is a segment of a road network.
 10. A devicecomprising a processor configured to execute a method for reducingintermediate nodes in a polygonal chain with one or a plurality ofintermediate nodes of a set of Intermediate nodes between a startingnode and an end node, wherein, in addition to the attributes oflongitude and latitude, at least one further attribute with an attributevalue and an attribute direction of a set of further attribute isassigned to the starting node, the end node and every intermediate nodeof the set of intermediate nodes, the method comprising: in one or moreprocessors, for each intermediate node, starting from the starting node:comparing the attribute direction of the at least one further attributeof an intermediate node with the attribute direct ion of the at leastone further attribute of the immediately preceding node; marking theintermediate node as a significant node if the comparison yields adirection change of the attribute direction; and applying a linegeneralization method with reference to the longitude and latitudeattributes, wherein the intermediate nodes that are marked assignificant nodes may not be removed.